The role of microbial inoculum in improving composting performance and promoting compost maturation: A review
Bibliographic record
Abstract
Accelerating the composting of organic waste remains a key objective in research and practice. This review aims to critically examine recent advancements in microbial inoculation (MI) strategies and their role in enhancing composting performance and promoting compost maturation. It synthesizes findings on microbial inocula, including single strains and consortia, and their effects on composting phases, microbial succession, and metabolic functions. It discusses the influence of MI on physicochemical parameters, such as moisture content, pH, temperature, and nutrient balance, and the impact on compost stability and humification. It addresses the impact of microplastics on microbial communities in composting, highlighting how microplastics can alter microbial dynamics and affect compost quality. The MI improves the efficiency of organic matter decomposition, shortens the time, enhances pathogen suppression, and produces higher-quality compost. Inoculations encourage enzyme synthesis, accelerate the breakdown of organic matter, elevate temperatures, boost humification, and enhance compost maturity. This review highlights the importance of MI in enhancing organic waste biotransformation, thereby contributing to sustainable waste management and resource recovery. It identifies research gaps and suggests future research directions, including large-scale inoculation trials, economic feasibility assessments, and the development of standardized microbial dosing protocols to support industrial and municipal composting systems. • Inoculants enhance decomposition, pathogen suppression, and compost quality. • Microbial augmentation accelerates degradation, producing stable and mature compost. • Optimizing inoculants and mitigating microplastic effects ensures compost viability. • Effective microbial strain selection and application methods remain underexplored. • Lack of studies on microplastic effects on microbial activity and compost quality.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".